Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A scalable modular convex solver for regularized risk minimization
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Large-Margin Discriminative Training of Hidden Markov Models for Speech Recognition
ICSC '07 Proceedings of the International Conference on Semantic Computing
Large margin training of acoustic models for speech recognition
Large margin training of acoustic models for speech recognition
A discriminative latent model of object classes and attributes
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Learning from partially annotated sequences
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
Hi, magic closet, tell me what to wear!
Proceedings of the 20th ACM international conference on Multimedia
Parsing collective behaviors by hierarchical model with varying structure
Proceedings of the 20th ACM international conference on Multimedia
Latent pyramidal regions for recognizing scenes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
View-Invariant action recognition using latent kernelized structural SVM
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Recognizing complex events using large margin joint low-level event model
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
GIANT: geo-informative attributes for location recognition and exploration
Proceedings of the 21st ACM international conference on Multimedia
Regularized bundle methods for convex and non-convex risks
The Journal of Machine Learning Research
Handling signal variability with contextual markovian models
Pattern Recognition Letters
Joint semi-supervised learning of Hidden Conditional Random Fields and Hidden Markov Models
Pattern Recognition Letters
Discriminative Hough context model for object detection
The Visual Computer: International Journal of Computer Graphics
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Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non-convexity of the optimization problem, previous works usually rely on severe approximations so that it is still an open problem. We propose a new learning algorithm that relies on non-convex optimization and bundle methods and allows tackling the original optimization problem as is. It is proved to converge to a solution with accuracy ε with a rate O (1/ε). We provide experimental results gained on speech and handwriting recognition that demonstrate the potential of the method.